Bi-clustering is a promising conceptual clustering approach. Within categorical data, it provides a collection of (possibly overlapping) bi-clusters, i.e., linked clusters for both...
A unifying model is presented that implies a categorical and/or dimensional reduction of one or several modes of a multiway data set. The model encompasses a broad range of (exist...
Training a classifier for object category recognition using images on the Internet is an attractive approach due to its scalability. However, a big challenge in this approach is ...
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...
We present a simple categorical semantics for ML signatures, structures and functors. Our approach relies on realizablity semantics in the category of assemblies. Signatures and s...